Parthenope University of Naples
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Energy analysis and greenhouse gas emissions intensity of green hydrogen production by a 1 MW innovative Proton Conducting Ceramic Electrolysis system
No full textDeep-Meg: A deep learning approach for magnetoencephalograhic inverse problem solutions
No full textThis manuscript introduces a deep learning algorithm designed for spatial and temporal source reconstruction based on signals captured by MEG devices. Estimating brain signals at the source level is a significant challenge in magnetoencephalographic (MEG) data processing. Traditional algorithms excel in temporal resolution but face limitations in spatial resolution due to the inherently ill-posed nature of the problem. However, precise localization of pathological tissues is often crucial for providing reliable information to clinicians, which makes this a key area for improvement. Deep learning solutions have emerged as promising candidates for high-resolution signal estimation in this context. The proposed approach, called 'Deep-MEG', utilizes a hybrid neural network architecture capable of extracting both temporal and spatial information from MEG sensor signals. Unlike traditional methods, the algorithm can handle the entire brain, making it suitable for imaging not just cortical sources but also subcortical ones. To validate its performance, the authors conducted simulations with multiple active sources using a realistic forward model and compared the results with those from various state-of-the-art reconstruction algorithms.Clinical relevance- This study represent a first approach for accurate deep source localization and reconstruction leading to diagnosis support to clinicians
Exploring the Role of Digital Twin and Industrial Metaverse Technologies in Enhancing Occupational Health and Safety in Manufacturing
No full textThe evolution of Industry 4.0 and the emerging paradigm of Industry 5.0 have introduced disruptive technologies that are reshaping modern manufacturing environments. Among these, Digital Twin (DT) and Industrial Metaverse (IM) technologies are increasingly recognized for their potential to enhance Occupational Health and Safety (OHS). However, a comprehensive understanding of how these technologies integrate to support OHS in manufacturing remains limited. This study systematically explores the transformative role of DT and IM in creating immersive, intelligent, and human-centric safety ecosystems. Following the PRISMA guidelines, a Systematic Literature Review (SLR) of 75 peer-reviewed studies from the SCOPUS and Web of Science databases was conducted. The review identifies key enabling technologies such as Virtual Reality (VR), Augmented Reality (AR), Extended Reality (XR), Internet of Things (IoT), Artificial Intelligence (AI), Cyber-Physical Systems (CPS), and Collaborative Robots (COBOTS), and highlights their applications in real-time monitoring, immersive safety training, and predictive hazard mitigation. A conceptual framework is proposed, illustrating a synergistic digital ecosystem that integrates predictive analytics, real-time monitoring, and immersive training to enhance the OHS. The findings highlight both the transformative benefits and the key adoption challenges of these technologies, including technical complexities, data security, privacy, ethical concerns, and organizational resistance. This study provides a foundational framework for future research and practical implementation in Industry 5.0
La tutela della (sola) genitorialità nelle vicende risolutive del rapporto: parità di genere “condizionata”, inderogabilità e negozi abdicativi
No full textIl settore dell'agroindustria in Italia. Caratteristiche strutturali, innovazione e politiche industriali
No full text
Independent minority directors against self‐serving and manipulative practices in non‐financial reporting
No full textLong Period Gratings Inscribed With Electric Arc in Nanostructured Optical Fibers and Their Sensitivity to Gamma Radiation
No full textIn this work, for the first time, we demonstrate long period gratings (LPG) in nanostructured optical fibers and their response to gamma radiation. Nanostructured fibers show distinctive features such as arbitrary gradient refractive index (RI) distributions in the core, core shapes without symmetry constraints, and engineered polarization properties as an intrinsic feature of the artificial glass material. Two nanostructured silica single mode optical fibers have been processed using the electric arc discharge technique to inscribe LPGs and the results have been compared with those for standard Ge-doped SMF28. The core of the first fiber shows a parabolic RI profile achieved arranging high-RI nanorods. The second fiber contains a core composed of silica and ytterbium-doped silica nanorods arranged as alternating layers of high- and low-RI (i.e., in a “ZEBRA” structure). First, a detailed analysis of the LPG formation during the inscription, polarization dependence and response to surrounding RI, temperature, and strain have been provided. Moreover, the impact of a 30 kGy gamma radiation dose has been evaluated in real time on these nanostructured fibers by monitoring the resonance wavelength shift. It has been found that nanostructured fibers can be effectively processed with electric arc towards LPG inscription in similar manner as standard fibers. Moreover, in the case of ZEBRA fiber a high sensitivity to gamma radiation can be obtained
Endocrine and Metabolic Mechanisms Linking Obesity to Type 2 Diabetes: Implications for Targeted Therapy
No full textObesity and Type 2 Diabetes Mellitus (T2DM) are interrelated chronic conditions whose global prevalence continues to rise, posing significant clinical and socioeconomic challenges. Their pathophysiological intersection—commonly referred to as “diabesity”—is sustained by a complex interplay of mechanisms, including visceral adipose tissue inflammation, macrophage polarization, disrupted insulin signaling, and adipokine imbalance. These processes contribute to chronic low-grade systemic inflammation, impair pancreatic β-cell function, and exacerbate glucose intolerance. This review critically explores the mechanistic connections between obesity and T2DM, with a focus on recent advances in pharmacological therapies—such as GLP-1 receptor agonists, SGLT2 inhibitors, and dual GIP/GLP-1 receptor agonists—alongside evidence-based lifestyle modifications and bariatric procedures. By integrating current translational and clinical findings, we aim to provide a comprehensive perspective to support the development of more effective and individualized treatment strategies for diabesity
Family firms and ESG performance: the role of generational stage
No full textPurpose
Despite the heterogeneity of family businesses in terms of generational ownership stage, scholars have paid little attention to this relevant factor when exploring environmental, social and governance (ESG) performance of family firms. So, drawing on socioemotional wealth (SEW) perspective, the purpose of this paper is to shed light on the propensity of family firms to engage in ESG practices and how it varies due to the generational stage.
Design/methodology/approach
This study describes the relationship between family firms and ESG performance (measured by Refinitiv ESG scores) by using a large sample of 24,302 European listed family and nonfamily firms. Following previous literature, family firms are those where family holds 20% or more of equity stake and at least a family member seats on the board of directors. This paper used an ordinary least squares regression approach, paired with a propensity score matching to solve potential endogeneity.
Findings
The main results indicate that ESG performances are higher in family firms compared to nonfamily counterparts. However, this study observed relevant differences when conditioning upon generational stage, with the previous result confirmed only for later generations, while founding generation’s firms negatively influenced ESG scores. These results are clear evidence of the de-emphasis on socioemotional considerations and family-centered goals as generational stage increases, leading to a greater attention toward external stakeholders.
Research limitations/implications
As this paper uses a European sample of listed firms, the results may be generalized with caution, especially when trying to extend them to the Anglo-Saxon capitalism, characterized by a greater ownership dispersion. In this respect, future studies could explore the role of the family-firm status on the ESG performance by further conditioning upon different types of ownership structures. Future avenue of research could also explore the effect of other governance mechanisms (i.e. the presence of outside independent members of the board) in shaping family members’ propensity to embrace sustainable business practices.
Practical implications
The results have several implications for investors, managers and policymakers. In fact, in searching for socially responsible investments, investors should be aware of the different motivations of family members (according to the generational stage) in boosting ESG performance. Similarly, ESG-oriented managers should be aware of the possible divergences with founding generation family owners in the adoption of ESG practices. Finally, policymakers should implement rules and incentives to stimulate founding generation family firms’ attitude toward ESG practices.
Originality/value
The findings advance the ESG literature by answering to the call of previous research pointing out the importance of exploring ESG behaviors in different organizational settings. In addition, this study contributes to the literature on family firms by demonstrating the importance of generational stages, as different stages are likely to be associated with different family incentives and goals, consistent with the SEW framework